Current AI in games : a review


Autoria(s): Sweetser, Penelope; Wiles, Janet
Data(s)

2002

Resumo

As the graphics race subsides and gamers grow weary of predictable and deterministic game characters, game developers must put aside their “old faithful” finite state machines and look to more advanced techniques that give the users the gaming experience they crave. The next industry breakthrough will be with characters that behave realistically and that can learn and adapt, rather than more polygons, higher resolution textures and more frames-per-second. This paper explores the various artificial intelligence techniques that are currently being used by game developers, as well as techniques that are new to the industry. The techniques covered in this paper are finite state machines, scripting, agents, flocking, fuzzy logic and fuzzy state machines decision trees, neural networks, genetic algorithms and extensible AI. This paper introduces each of these technique, explains how they can be applied to games and how commercial games are currently making use of them. Finally, the effectiveness of these techniques and their future role in the industry are evaluated.

Formato

application/pdf

Identificador

http://eprints.qut.edu.au/45741/

Publicador

ANU

Relação

http://eprints.qut.edu.au/45741/1/AJIIPS_paper.pdf

http://cs.anu.edu.au/ojs/index.php/ajiips

Sweetser, Penelope & Wiles, Janet (2002) Current AI in games : a review. Australian Journal of Intelligent Information Processing Systems, 8(1), pp. 24-42.

Direitos

Copyright 2002 [please consult the author]

Fonte

Computer Science; Faculty of Science and Technology

Palavras-Chave #080100 ARTIFICIAL INTELLIGENCE AND IMAGE PROCESSING #080300 COMPUTER SOFTWARE #computer games #artificial intelligence
Tipo

Journal Article